US6549653B1 - Color image processing apparatus - Google Patents

Color image processing apparatus Download PDF

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US6549653B1
US6549653B1 US09/152,974 US15297498A US6549653B1 US 6549653 B1 US6549653 B1 US 6549653B1 US 15297498 A US15297498 A US 15297498A US 6549653 B1 US6549653 B1 US 6549653B1
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color
spectral reflectance
color image
calculating
data
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Kenro Osawa
Nagaaki Ohyama
Masahiro Yamaguchi
Takashi Obi
Yuri Ohya
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Olympus Corp
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Olympus Optical Co Ltd
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Priority to US10/395,350 priority Critical patent/US7010162B2/en
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Priority to US11/272,609 priority patent/US7251362B2/en
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/46Colour picture communication systems
    • H04N1/56Processing of colour picture signals
    • H04N1/60Colour correction or control
    • H04N1/6083Colour correction or control controlled by factors external to the apparatus
    • H04N1/6088Colour correction or control controlled by factors external to the apparatus by viewing conditions, i.e. conditions at picture output
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/46Colour picture communication systems
    • H04N1/56Processing of colour picture signals
    • H04N1/60Colour correction or control
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/46Colour picture communication systems
    • H04N1/56Processing of colour picture signals
    • H04N1/60Colour correction or control
    • H04N1/603Colour correction or control controlled by characteristics of the picture signal generator or the picture reproducer
    • H04N1/6033Colour correction or control controlled by characteristics of the picture signal generator or the picture reproducer using test pattern analysis
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/46Colour picture communication systems
    • H04N1/56Processing of colour picture signals
    • H04N1/60Colour correction or control
    • H04N1/6083Colour correction or control controlled by factors external to the apparatus
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/46Colour picture communication systems
    • H04N1/56Processing of colour picture signals
    • H04N1/60Colour correction or control
    • H04N1/6083Colour correction or control controlled by factors external to the apparatus
    • H04N1/6086Colour correction or control controlled by factors external to the apparatus by scene illuminant, i.e. conditions at the time of picture capture, e.g. flash, optical filter used, evening, cloud, daylight, artificial lighting, white point measurement, colour temperature
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/80Camera processing pipelines; Components thereof
    • H04N23/84Camera processing pipelines; Components thereof for processing colour signals
    • H04N23/88Camera processing pipelines; Components thereof for processing colour signals for colour balance, e.g. white-balance circuits or colour temperature control
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09GARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2320/00Control of display operating conditions
    • G09G2320/02Improving the quality of display appearance
    • G09G2320/0271Adjustment of the gradation levels within the range of the gradation scale, e.g. by redistribution or clipping
    • G09G2320/0276Adjustment of the gradation levels within the range of the gradation scale, e.g. by redistribution or clipping for the purpose of adaptation to the characteristics of a display device, i.e. gamma correction
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09GARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G5/00Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators
    • G09G5/02Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators characterised by the way in which colour is displayed

Definitions

  • the present invention relates to a color image processing apparatus which estimates the spectral reflectance of an object to be shot, from a color image signal.
  • an image display apparatus such as a CRT monitor or a printing device such as a printer
  • a color image signal input device such as a color scanner or a digital camera
  • the values of XYZ color system which is represented by the following equation (1) using functions of wavelength ⁇ , x( ⁇ ), y( ⁇ ) and z( ⁇ ), corresponding to the spectral sensitivities of human vision, which is called as color matching function as defined by Commission International de I'Eclairage (CIE), and the spectrum of an object w( ⁇ ), or a uniform color space based on the XYZ color system are widely used.
  • CIE Commission International de I'Eclairage
  • K is a constant.
  • the problem is to estimate the XYZ values of the object under the illumination used for acquiring the color image signal.
  • the conversion relationship can be obtained from the relationship between the spectral sensitivities of the input device and the color matching functions; however it can be indirectly obtained from the relation between color image signals of three or more objects having independent XYZ values, and measured XYZ values.
  • the conversion relationship can be obtained by a way of least square method from the relationship between the color image signals and XYZ values for a number of colors of objects.
  • the format of the color chart used as the object for obtaining color data from a color image signal acquired by the input device is standardized by ISO IT8.7, and provided by several film makers.
  • the product of the spectral sensitivities of the input device and the shooting-site illumination spectrum, and the product of the color matching functions and the observation-site illumination spectrum must have the relationship of linear conversions.
  • the method of obtaining the spectral reflectance of an object by estimating the spectrum from a lot of multi-channel images acquired by the spectral sensitivities of narrow bands, and dividing the estimated spectrum by illumination spectrum can be proposed as disclosed in, for example, Jpn. Pat. Appln. KOKAI Publication No. 9-172649.
  • the data of the spectrum of the illumination used to acquire the color image signal is necessary in addition to the spectral sensitivities of the input device.
  • a measurement device such as a spectrophotometer is required when shooting, and therefore these method cannot be easily applied to a system which employs a conventional color image input device.
  • the object of the present invention is to provide a color image processing device capable of estimating the spectral reflectance of an object to be shot from the color image signal of the object acquired by a color image signal input device, even if the spectral sensitivities of the color image signal input device, or the spectrum of the illumination used when the color image signal is input are unknown.
  • a color image processing device including image processing means for subjecting an image signal input of an object to be shot, to a predetermined image processing, so as to be able to reproduce color data of the object, wherein the image processing means carries out the process of reproducing the color data of the object, by estimating the spectral reflectance of the object using the color image signal of a reference object the spectral reflectance of which is known, the color image signal of an object acquired by the same illumination condition as that for acquiring the color image signal of the reference object, and the spectral reflectance data of the reference object.
  • FIG. 1 is a diagram showing a structure of a color image processing device according to the first embodiment of the present invention
  • FIG. 2 is a diagram showing a detailed structure of an image processing device in the color image processing device according to the first embodiment
  • FIG. 3 is a diagram showing a structure of an object expansion coefficient calculating unit shown in FIG. 2;
  • FIG. 4 is a diagram showing a structure of a spectral reflectance calculating unit shown in FIG. 2;
  • FIG. 5A is a diagram showing a structure of the color image input device shown in FIG. 1;
  • FIG. 5B is a diagram showing a structure of a filter turret to which interference filters are mounted and which are built in the color image input device;
  • FIG. 6 is a diagram showing a structure of an RGB value calculating unit shown in FIG. 2;
  • FIG. 7 is a diagram showing an example of a reference chart used in the present invention.
  • FIG. 8 is a diagram showing a structure of a color image processing device according to the second embodiment of the present invention.
  • FIG. 9 is a diagram showing a detailed structure of a image processing device in the color image processing device according to the second embodiment.
  • FIG. 10 is a diagram showing a structure of an object expansion coefficient calculating unit shown in FIG. 9;
  • FIG. 11 is a diagram showing a structure of a spectral reflectance calculating unit shown in FIG. 9;
  • FIG. 12 is a diagram showing a structure of a color image processing device according to the third embodiment of the present invention.
  • FIG. 13 is a diagram showing a detailed structure of an image processing device in the color image processing device according to the third embodiment.
  • FIG. 14 is a diagram showing a structure of an object expansion coefficient calculating unit shown in FIG. 13;
  • FIG. 15 is a diagram showing a structure of a color image processing device according to the fourth embodiment of the present invention.
  • FIG. 16 is a diagram showing a structure of a spectral reflectance evaluating unit shown in FIG. 15;
  • FIG. 17 is a diagram showing a structure of a color image processing device according to the fifth embodiment of the present invention.
  • FIG. 18 is a diagram showing a concept of a format of shot image data stored on a memory card.
  • FIG. 19 is a diagram illustrating a color conversion process in the fifth embodiment.
  • the spectral reflectance of an object is estimated from the spectral reflectance of reference objects whose spectral reflectances are known a priori and color image signal values of the reference objects and color image signal values of the object whose spectral reflectance is not known acquired from the color image signal input device (to be called simply “input device” hereinafter).
  • the spectrum of the illumination for shooting is represented by S( ⁇ )
  • the spectral reflectance of the object is represented by p( ⁇ )
  • a signal value q k obtained by shooting an object under the shooting-site illumination at the k-th camera sensitivity is given by the following formula supposing that the sensitivity of the camera makes a linear response to the intensity of incident light:
  • Q is a matrix known by measurement, and therefore when A is available, the value for C can be obtained.
  • C it becomes possible to obtain the spectral reflectance p( ⁇ ) of the object from the formula (3).
  • the M-number of color chips whose spectral reflectances are known are shot.
  • the shooting signal value g km of the m-th color chip by the k-th camera sensitivity is given by:
  • the basis function el( ⁇ ) can be represented by the following formula using the expansion coefficient Oln.
  • ⁇ l( ⁇ ) is an expansion error.
  • Q represents a shooting signal of an object
  • O represents an expansion coefficient obtained by expanding the basis functions of the spectral reflectance of the object by the basis functions of the spectral reflectances of the color chips
  • B represents the expansion coefficient of the basis function of each spectral reflectance of the color chips
  • G represents a shooting signal of the color chips.
  • G By shooting a color chips whose spectral reflectances are known, G is obtained.
  • G is obtained.
  • an expansion coefficient B of the basis functions of each spectral reflectance of the color chips which are obtained in advance an expansion coefficient O of the basis functions of the spectral reflectances of an object which is calculated in advance and a shooting signal Q of an object, the expansion coefficient of the basis functions for the spectral reflectance of an object can be obtained.
  • the basis functions for the spectral reflectance of the object and the expansion coefficient C the spectral reflectance of the object is calculated.
  • the spectral reflectance of the object can be obtained from the shooting signal Q of the signal using a color chip shooting image signal G shot by a camera having the same number of bands as the number of the basis functions.
  • the spectral reflectance of an object can be expanded by the basis functions of the color chips
  • the spectral reflectance of the object can be obtained as a linear combination of the basis functions of the spectral reflectances of the color chips, by rendering C′ of the formula (21) the expansion coefficient of the basis functions of the spectral reflectance of the color chips.
  • the spectral reflectance of an object can be obtained by a camera having bands whose number is equal to or more than that of the basis functions of the spectral reflectances of the color chips. Further, if the basis functions of the spectral reflectances of the object are known, and it can be expanded by the basis functions of the spectral reflectances of the color chips, the spectral reflectance of the object can be obtained by the formula (20) from the shooting signal Q of the object, using the color chip shooting image signal G taken by a camera having bands whose number is equal to or more than that of the basis functions of the object.
  • el′( ⁇ ) is expanded by vn′( ⁇ )
  • Q represents a shooting signal of an object
  • O′ represents an expansion coefficient obtained by expanding the product of the basis functions of the spectral reflectance of an object and the object shooting-site illumination spectrum
  • B represents the expansion coefficient of the basis function of each spectral reflectance of the color chips
  • G represents a shooting signal of the color chips.
  • the spectral reflectance of the object can be calculated from its basis functions and expansion coefficients.
  • the spectral reflectance of an object is estimated from the shooting signal of the object, having the basis functions of the spectral reflectance, by which the basis function of the spectral reflectance of the object can be expanded.
  • the spectral reflectance of the object can be estimated from the shooting signal of the object if the color chip shooting-site illumination spectrum and object shooting-site illumination spectrum are known.
  • the method can be applied to a 3-band input device.
  • the color chip As a reference object whose spectral reflectance is known, the color chip has been discussed as an example; however arbitrary objects can be applied to this method as long as they have spectral reflectances similar to those of the color chips.
  • FIG. 1 is a diagram showing an example of the structure of a color image processing apparatus according to the first embodiment of the present invention, which will now be described.
  • the apparatus of this embodiment includes a color image input device (input device) 1 , a reference chart 2 and an object 3 , arranged under the same illumination A, an observation-site illumination spectrum data storage unit 4 , an image processing device 5 and a CRT monitor 6 .
  • the image processing device 5 shoots the reference chart 2 and the object 3 arranged under the same illumination A in order or at the same time by the input device 1 . Further, the spectral reflectance and XYZ values of the object 3 are estimated from the image signals G and Q output, and the basis functions and expansion coefficients data of the reflectances of color chips, and color matching functions data, which are present in advance within the image processing device, and thus RGB signals are output.
  • the RGB signals are displayed on the CRT monitor 6 as a color image of the object.
  • the XYZ values under the observation-site illumination are obtained from the spectral reflectance of the object, which is estimated by the image processing device 5 , and further the data is displayed on the CRT monitor as a color image.
  • the present invention is not limited to this embodiment, but is applicable to the system including display devices such as a liquid crystal display device and a plasma display, and a printing device such as a color printer. Further, it is possible to store the spectral reflectance and XYZ values as data.
  • the image signal of the reference chart 2 is extracted from the object shooting signal by a reference chart extracting device (not shown). in the image processing device 5 .
  • the input device 1 forms an image on a semiconductor imaging device such as a CCD 104 , from the transmitted light through a camera lens 1 and one of a plurality of interference filters 103 mounted on the filter turret 102 .
  • a semiconductor imaging device such as a CCD 104
  • interference filters 103 are mounted on the filter turret 102 having a circular shape, as schematically shown in FIG. 5 B. As the filter turret 102 is rotated by the motor 105 , each of the interference filters 103 is mounted on the rear surface of the camera lens 101 in order, and an image of the corresponding band is shot by the CCD 104 .
  • the CCD 104 has the pixel number of, for example, 640 pixels ⁇ 480 pixels. Naturally, the present invention is not limited to this pixel number.
  • the output signal of an image shot by the CCD 104 is sent to the image processing device 5 .
  • FIG. 7 shows an example of the reference chart 2 .
  • the reference chart 2 consists of 10 color chips, and the spectral reflectance of each color chip can be expanded by 10 basis functions which are independent from each other.
  • the image signals G and Q acquired by the input device 1 are input to the image processing device 5 as 10 channels image data having a pixel size of 640 pixels ⁇ 480 pixels of 10-bits per pixel.
  • observation-site illumination spectrum data is input from the observation-site illumination spectrum data storage unit 4 .
  • the observation-site illumination spectrum data consists of light intensity values of observation-site illumination taken at an interval of 1 nm, in a wavelength range from 380 nm to 780 nm.
  • the image processing device 5 the spectral reflectance and the XYZ values of the object are estimated from these input data, and the color chip basis function data, color chip expansion coefficient data and color matching functions data, which are pre-stored in the image processing device. Further, the image processing device 5 converts, on the basis of the characteristics data of the CRT monitor 6 , the XYZ values of the object 3 taken under the observation-site illumination into RGB signals to be displayed on the monitor screen, and outputs the signals to the CRT monitor 6 .
  • the CRT monitor 6 displays the color image of the object.
  • the image processing device 5 consists mainly of a spectral reflectance calculating unit 7 , a tristimulus value calculating unit 8 and an RGB value calculating unit 9 .
  • the spectral reflectance calculating unit 7 comprises of a color chip shooting signal storage unit 11 , a color chip expansion coefficient storage unit 12 , an object expansion coefficient calculating unit 10 , a color chip basis function storage unit 14 and a spectral reflectance calculating unit 13 for calculating a spectral reflectance p( ⁇ ).
  • the color chip shooting signal storage unit 11 calculates, from the shooting image of the reference chart containing a plurality of color chips, the average values of shooting signal values corresponding to the color chips, for an appropriate region, and stores them as color chip shooting signals.
  • the color chip expansion coefficient storage unit 12 stores expansion coefficients corresponding to basis functions of the spectral reflectances of the color chips in the reference chart, which are obtained in advance.
  • the object expansion coefficient calculating unit 10 calculates an expansion coefficient C of the spectral reflectance of an object from the object shooting signal input from the color image input device 1 , the color chip shooting signal G input from the color chip shooting signal storage unit 11 and the expansion coefficient B input from the color chip expansion coefficient storage unit 12 .
  • FIG. 3 shows the structure of the object expansion coefficient calculating unit 10 , which will now be described.
  • An inverse matrix B ⁇ 1 of the expansion coefficient B calculated by an inverse matrix operating unit A 19 , from the expansion coefficient B input from the color chip expansion coefficient storage unit 12 , and a color chip shooting signal G input from the color chip shooting signal storage unit 11 are input to a matrix multiplication unit A 20 , and thus a matrix (GB ⁇ 1 ) is calculated.
  • the calculated GB ⁇ 1 is input to an inverse matrix operating unit B 21 to obtain an inverse matrix thereof (GB ⁇ 1 ) ⁇ 1 , which is input to a matrix multiplication unit B 22 .
  • FIG. 4 shows the structure of the spectral reflectance calculating unit 13 , which will now be described.
  • the spectral reflectance calculating unit 13 consists of a basis coefficient multiplication unit 23 for multiplying an object expansion coefficient C corresponding to a color chip basis function vn( ⁇ ), and a basis function integrating unit 24 for calculating the spectral reflectance.
  • the tristimulus value operating unit 16 calculates the tristimulus values XYZ under the illumination condition for observing an object, from the spectral reflectance of the object, calculated from the spectral reflectance calculating unit 7 , the observation-site illumination input from the observation-site illumination spectrum data storage unit 4 , and the color matching function data pre-stored in the color matching function data storage unit 15 , and the values are output to the RGB value calculating unit 9 .
  • the RGB value calculating unit 9 comprises a CRT monitor profile storage unit 17 for storing the characteristics data of the display device and an output signal calculating unit 18 for converting the XYZ values to the monitor input signal RGB values using the characteristics data of the CRT monitor.
  • the characteristics data of the CRT monitor contains a matrix M stored in the phosphor tristimulus value data storage unit 25 and a gamma curve ⁇ R ⁇ G ⁇ B stored in the RGB gradation characteristics data storage unit 26 .
  • the matrix M is a matrix made of elements of 3 ⁇ 3, and the gamma curves ⁇ R ⁇ G ⁇ B is the output luminance value to each of the RGB input values.
  • the RGB value calculating unit 9 the XYZ value calculated by the tristimulus values calculating unit 8 and the matrix M stored in the phosphor tristimulus value data storage unit 25 are multiplied by the matrix multiplication unit 27 . Then, the gradation correcting unit 28 performs the correction of the gradation on the basis of the result of the multiplication and the gamma curves stored in the RGB gradation characteristics data storage unit 26 , and thus the RGB signals are obtained by conversion.
  • the calculated RGB signals are input to the CRT monitor, and a color image of the object is displayed on the CRT monitor.
  • the spectral reflectance of an object is estimated from the object shooting signal Q and reference chart shooting signal G shot under the same illumination condition by the color image input device, and the color chip basis functions vn( ⁇ ), which can expand the spectral reflectance of the spectral reflectance of all the color chips of the reference chart pre-stored, (that is, the spectral reflectance data of the object) and the expansion coefficients B of the color chips.
  • the conditions for being able to estimate the spectral reflectance of an object exactly are that the spectral reflectance of the object can be expanded by the color chip basis functions vn( ⁇ ) of the reference chart and the color image input device has the number of bands which is equal to or more than that of color chip basis functions. With these conditions, the spectral reflectance of an object can be estimated even if the spectral sensitivities of the color image input device and the illumination spectrum used for shooting are unknown.
  • FIG. 8 shows a color image processing apparatus according to the second embodiment of the present invention.
  • the apparatus of this embodiment consists of an input device 1 to which a color image is input by shooting, a reference chart 2 and an object 3 , which are arranged under the same illumination A, an observation-site illumination spectrum data storage unit 4 for storing observation-site illumination spectrum data, an object basis function storage unit 29 for storing object basis function el( ⁇ ), an image processing device 30 for outputting RGB signals and a CRT monitor 6 for displaying a color image.
  • the image processing device 30 shoots the reference chart 2 and object 3 , which are exposed by the same illumination A sequentially or at the same time, by the input device 1 , and estimates the spectral reflectance and XYZ values of the object 3 from the shooting signals G and Q of those shot respectively, and the color chip basis functions data, color chip expansion coefficients data and color matching functions data, pre-stored in the image processing device.
  • the RGB signals are output.
  • the RGB signals are displayed on the CRT monitor 6 as a color (RGB) image of the object.
  • the input device 1 is equivalent to the input device of the first embodiment described above, and a filter turret on which interference filters are arranged, as shown in FIGS. 5A and 5B, is mounted. Further, the reference chart of this embodiment has the same structure as shown in FIG. 7 . Therefore, the explanations therefor will not be repeated.
  • the observation-site illumination spectrum data consists of intensity values of observation-site illumination taken at an interval of 1 nm, in a wavelength range from 380 nm to 780 nm.
  • the spectral reflectance and XYZ values of the object are estimated from these input data, the color chip expansion coefficient B pre-stored in the image processing device, the expansion coefficient O obtained by expanding the basis function of an object by the basis functions of the color chips, the color chip basis functions vn( ⁇ ), and the color matching functions data.
  • RGB signals to be input to the CRT monitor are output; the RGB signals are used for displaying the XYZ values of the object taken under the observation-site illumination, on the CRT monitor, using the characteristics data of the CRT monitor.
  • the CRT monitor displays a color image of the object, as the RGB signal output from the image processing device is input thereto.
  • the image processing device 30 consists mainly of a spectral reflectance calculating unit 31 , a tristimulus value calculating unit 8 and an RGB value calculating unit 9 .
  • the structural elements of this embodiment which are similar to those shown in FIG. 2, will be designated by the same reference numerals, and the detailed descriptions therefor will not be repeated.
  • the object shooting signal Q and reference chart shooting signal G output from the color image input device 1 are input to the object expansion coefficient calculating unit 33 and the color chip shooting signal storage unit 11 respectively.
  • the color chip shooting signal storage unit 11 from a reference chart image made of a plurality of color chips, average values of the shooting signals for all the color chips are calculated in an appropriate region, and the calculation result is stored as a color chip shooting signal.
  • the color chip expansion coefficient storage unit 12 expansion coefficients for the basis functions of the color chips within a reference color chip obtained in advance are stored.
  • the expansion coefficient O in the case of expanding the object basis function el( ⁇ ) by the color basis function vn( ⁇ ) is obtained.
  • the spectral reflectance calculating unit 13 calculates the spectral reflectance p( ⁇ ) of the object from the expansion coefficient C and the basis functions el( ⁇ ) output from the object basis function storage unit 29 .
  • FIG. 10 shows the structure of the object expansion coefficient calculating unit 33 , which will now be described.
  • the inverse matrix B ⁇ 1 of the expansion coefficient B which is calculated by the inverse matrix operating unit A 34 from the expansion coefficient B input from the color chip expansion coefficient storage unit 12 , the color chip shooting signal G input from the color chip shooting signal storage unit 11 , and the expansion coefficient O input from the object basis expansion coefficient calculating unit 32 are input to the inverse Matrix Multiplication unit A 35 , and thus matrix GB ⁇ 1 O is calculated.
  • the obtained matrix GB ⁇ 1 O is input to the inverse matrix operating unit B 36 , and thus an inverse matrix (GB ⁇ 1 O) ⁇ 1 is obtained, which is further input to the matrix multiplication unit B 37 .
  • the object shooting signal Q is further input.
  • the spectral reflectance p( ⁇ ) of the object is calculated on the basis of the expansion coefficient C calculated from the object expansion coefficient calculating unit 33 and the basis functions el( ⁇ ) of the object, which is output from the object basis function storage unit 29 .
  • FIG. 11 shows the structure of the spectral reflectance calculating unit 13 , which will now be described.
  • the spectral reflectance calculating unit 13 includes a basis coefficient multiplication unit 38 for multiplying the object basis functions el( ⁇ ) with the corresponding object expansion coefficient C, and a basis function integrating unit 24 for calculating the spectral reflectance.
  • the tristimulus value operating unit 16 calculates the tristimulus values XYZ under the illumination condition for observing the object on the basis of the spectral reflectance of the object, calculated in the spectral reflectance calculating unit 13 , the observation-site illumination spectrum data input from the observation-site illumination spectrum data storage unit 4 and the color matching functions data pre-stored in the color matching function data storage unit 15 .
  • the output signal calculating unit 18 converts the XYZ values calculated in the tristimulus value calculating unit 8 into an RGB signals to be input to the monitor, with use of the characteristics data of the CRT monitor, pre-stored in the CRT monitor profile storage unit 17 .
  • the characteristics data of the CRT monitor includes a matrix M stored in the phosphor tristimulus value data storage unit 25 shown in FIG. 6 and gamma curves ⁇ R ⁇ G ⁇ B stored in the RGB gradation characteristics data storage unit 26 .
  • the matrix M is a matrix consisting of elements arranged in 3 ⁇ 3, and the gamma curves ⁇ R ⁇ G ⁇ B are output light intensity to respective input RGB values.
  • the RGB signals output from the RGB value calculating unit 9 are input to the CRT monitor 6 , and the color image of the object is displayed on the CRT monitor 6 .
  • the spectral reflectance of an object is estimated from the object shooting signal Q and reference chart shooting signal G, shot by the color image input device, the color chip basis functions vn( ⁇ ) which can expand the spectral reflectance of every color chip of the reference chart pre-stored, the expansion coefficient B of each color chip and the basis function el( ⁇ ) of the spectral reflectance of the object.
  • the conditions for being able to estimate the spectral reflectance of an object without error are that the basis functions el( ⁇ ) of the spectral reflectance of an object can be expanded by the color chip basis functions vn( ⁇ ) of the reference chart, and that the color image input device has a certain number of bands, which is more than the number of basis functions of the spectral reflectances of the object.
  • the spectral sensitivities of the color image input device and the illumination spectrum for shooting are not known, the spectral reflectance of the object can be estimated.
  • the second embodiment is different from the first one in that the number of bands which is required by the color image input device in order to accurately estimate the spectral reflectance of the object, is not the number of color chip basis functions, but the number of basis functions of the reflectance of the object.
  • the number of basis functions of the spectral reflectance of the object is less than the number of basis functions of the spectral reflectances of the color chips, which can expand the basis function of the spectral reflectance of the object. Therefore, it becomes possible to estimate the spectral reflectance of the object by a camera having the less number of bands than that of the first embodiment. Further, a great number of color chips can be used to be able to expand the spectral reflectance of an object at high accuracy, while maintaining the number of bands of the camera for shooting an object equal to the number of basis functions of the spectral reflectance of the object.
  • FIG. 12 shows the structure of the color image processing apparatus according to the third embodiment of the present invention, which will now be described.
  • the device of this embodiment includes a color image input device 1 for inputting a color image by shooting or the like, a reference chart 2 a placed under illumination A, an object 3 a placed under illumination B different from the illumination A, an observation-site illumination spectrum data storage unit 4 for storing observation-site illumination spectrum data, an object basis function storage unit 29 for storing an object basis function el( ⁇ ), an object shooting-site illumination spectrum data storage unit 39 for storing object shooting-site illumination spectrum data, which will be explained later, a reference chart shooting-site illumination spectrum data storage unit 40 for storing reference chart shooting-site illumination spectrum data, an image processing device 41 for estimating a spectral reflectance and an XZY values of an object 3 a from image signals G and Q of the reference chart 2 a and object which are shot, and for outputting RGB signals, and a CRT monitor 6 for displaying the XYZ values of the object under the observation-site illumination, from the RGB signals.
  • a color image input device 1 for inputting a color image by shooting or the like
  • the input device 1 is equivalent to the input device of the first embodiment, and a filter turret on which interference filters shown in FIGS. 5A and 5B are arranged is mounted in the input device 1 . Further, this embodiment has an equivalent structure to that shown in FIG. 7 in terms of the reference chart, and therefore the explanations therefor will not be repeated.
  • the illumination spectrum data are intensity values of illumination taken at an interval of 1 nm within a wavelength range of 380 nm to 780 nm.
  • the basis functions data of the object are input from the object basis function storage unit 29 .
  • the image processing device 41 estimates the spectral reflectance and XYZ values of an object from the above-described inputs, the color chip expansion coefficient B pre-stored in the image processing device, the expansion coefficient O′ obtained by expanding the products of the basis functions of the object and the object shooting-site illumination spectrum by the products of the basis functions of the color chips and the reference chart shooting-site illumination spectrum, the basis functions el( ⁇ ) of the object and the color matching function data. Further, with reference to the characteristics data of the CRT monitor 6 , the device 41 outputs the XYZ values of the object under the observation-site illumination, as RGB signals, to the CRT monitor 6 . The CRT monitor 6 displays the color image of the object on the basis of the RGB signals.
  • FIG. 13 shows an example of the structure of the image processing device 41 , which will now be described.
  • the image processing device 41 consists mainly of a spectral reflectance calculating unit 42 , a tristimulus value calculating unit 8 and an RGB value calculating unit 9 .
  • a spectral reflectance calculating unit 42 a spectral reflectance calculating unit 8 , a tristimulus value calculating unit 8 and an RGB value calculating unit 9 .
  • the structural elements of this embodiment which are similar to those shown in FIG. 9, will be designated by the same reference numerals, and the detailed descriptions therefor will not be repeated.
  • the object basis expansion coefficient calculating unit 43 calculates an expansion coefficient O′ of the case where the products of the object basis functions el( ⁇ ) and the object shooting-site illumination spectrum, that is, el( ⁇ ) ⁇ So( ⁇ ), is expanded by the products of the color chip basis functions vn( ⁇ ) and the reference chart shooting-site illumination spectrum, that is, vn( ⁇ ) ⁇ Sc( ⁇ ).
  • FIG. 14 shows the structure of the object expansion coefficient calculating unit 44 , which will now be described.
  • the inverse matrix B ⁇ 1 of the expansion coefficient B which is calculated by the inverse matrix operating unit A 34 from the expansion coefficient B input from the color chip expansion coefficient storage unit 12 , the color chip shooting signal G input from the color chip shooting signal storage unit 11 , and the expansion coefficient O′ input from the object basis expansion coefficient calculating unit 43 are input to the matrix multiplication unit A 45 , and thus matrix GB ⁇ 1 O′ is calculated.
  • the object shooting signal Q is further input.
  • the inverse matrix (GB ⁇ 1 O′) ⁇ 1 output from the inverse matrix operating unit B 36 the expansion coefficient of the object, C′ is calculated, and the result of the calculation is output to the spectral reflectance calculating unit 13 .
  • the spectral reflectance p( ⁇ ) of the object is calculated on the basis of the expansion coefficient C′ calculated from the object expansion coefficient calculating unit 44 and the basis functions el( ⁇ ) of the object, which are output from the object basis function storage unit 29 . Then, the result of the calculation is output to the tristimulus value calculating unit 8 .
  • the spectral reflectance calculating unit 13 has the same structure as illustrated in FIG. 11, and therefore the explanation of this unit will not be repeated.
  • the tristimulus value calculating unit 8 calculates the tristimulus values XYZ under the illumination condition for observing the object 3 a on the basis of the spectral reflectance of the object, calculated in the spectral reflectance calculating unit 42 , the observation-site illumination spectrum data input from the observation-site illumination spectrum data storage unit 4 and the color matching functions data pre-stored in the color matching function data storage unit 15 . Then, the calculated value is output to the output signal calculating unit 18 .
  • the output signal calculating unit 18 converts the XYZ values calculated in the tristimulus value calculating unit 8 into RGB signals to be input to the monitor, with use of the characteristics data of the CRT monitor 6 , pre-stored in the CRT monitor profile storage unit 17 . Thus, the color image is displayed on the CRT monitor 6 .
  • the spectral reflectance of an object is estimated from the object shooting signal Q and reference chart shooting signal G, shot by the color image input device under different illumination conditions, the color chip basis functions vn( ⁇ ) which can expand the spectral reflectance of every color chip of the reference chart pre-stored, the expansion coefficient B of each color chip, the basis function of the spectral reflectance of the object, the reference chart shooting-site illumination spectrum data and the object shooting-site illumination data.
  • the conditions for being able to estimate the spectral reflectance of an object without error are that the products of the basis functions of the spectral reflectance of the object and the object shooting-site illumination spectrum, can be expanded by the products of the color chip basis functions vn( ⁇ ) of the spectral reflectance of reference chart and the reference chart shooting-site illumination spectrum, and that the color image input device has a certain number of bands, which is more than the number of basis functions of the spectral reflectance of the object.
  • the third embodiment is different from the second one mainly in the following point. That is, even if the reference chart shooting-site illumination and the object shooting-site illumination are different from each other, the spectral reflectance of an object can be accurately estimated when the spectra of these illumination are known and the above conditions are satisfied.
  • the color chips image is shot in advance under a known illumination source and stored. Therefore, it becomes possible to estimate the spectral reflectance of an object when shooting the object with use of the same color image input device for shooting the color chips, without shooting the color chips.
  • the color image processing apparatus includes a basis function storage unit 46 for storing basis functions of the spectral reflectance of human skin, an expansion coefficient setting unit 47 for setting an expansion coefficient corresponding to a basis function, a spectral reflectance calculating unit 48 for calculating a spectral reflectance, a spectral reflectance evaluating unit 49 for judging if a calculated spectral reflectance satisfies an evaluation condition, and a spectral reflectance storage unit 50 for storing a spectral reflectance which satisfies an evaluation condition.
  • the basis functions of the spectral reflectance of the human skin which has values at an interval of 1 nm within a wavelength range from 380 nm to 780 nm.
  • the number of basis functions stored in the basis function storage unit 46 is determined in accordance with the contribution rate of the basis function obtained by principal component analysis of a great number of the spectral reflectances of human skin measured in advance by the measurement instrument.
  • the M-number of basis functions which are required to achieve a contribution rate of 99.9999% or more, are stored.
  • the spectral reflectance calculating unit 48 calculates the spectral reflectance from the data input thereto, that is, the M-number of basis functions stored in the basis function storage unit 46 and the M-number of expansion coefficients set by the expansion coefficient setting unit 47 .
  • the spectral reflectance evaluation unit 49 judges if the spectral reflectance satisfies the evaluation condition preset in the spectral reflectance evaluation unit 49 . If the condition is satisfied, the spectral reflectance is output to the spectral reflectance storage unit 50 , whereas if the condition is not satisfied, the expansion coefficient is reset in the expansion coefficient setting unit 47 . This operation is repeated until the M-number of spectral reflectances are output.
  • the spectral reflectance evaluation unit 49 includes a non-negative condition evaluation unit 52 and a preparation condition evaluation unit 53 . With this structure, the spectral reflectance calculated by the spectral reflectance calculating unit 48 is input thereto, and whether or not the spectral reflectance has a negative value is examined in the non-negative condition evaluation unit 52 .
  • the spectral reflectance data is sent to the preparation condition evaluation unit 53 , whereas in the case where there is a negative value in the range, negative value wavelength data is output to the expansion coefficient setting unit 47 .
  • the preparation condition evaluation unit 53 evaluates whether or not the spectral reflectance data sent from the non-negative condition evaluation unit 52 can be designed with available colorant which are stored as a data base in the colorant data storage unit 51 at an accuracy within an allowable error range.
  • the colorant data storage unit 51 stores the diffusion coefficient and absorption coefficient of available colorant in the form of data base.
  • the spectral reflectance closest to the one which can be designed from these data is calculated.
  • the spectral reflectance sent from the non-negative condition evaluation unit 52 satisfies an accuracy within an allowable error range for the spectral reflectance data which can be designed by these colorant
  • the spectral reflectance data is stored in the spectral reflectance storage unit 50 .
  • the data cannot be designed, it is output as design error data to the expansion coefficient setting unit 47 .
  • the color chip having a spectral reflectance prepared in this embodiment is used as an object whose spectral reflectance is known in the first to third embodiments, it becomes possible to estimate the spectral reflectance of an object at higher accuracy.
  • FIG. 17 schematically shows the structure of the embodiment.
  • an object (human image) shot by the digital camera 54 and an image of the reference chart 55 prepared for human skin, which were taken under the shooting-site illumination are shot as one image.
  • the shooting image data is written in a memory card 56 provided within the digital camera 54 .
  • the memory card 56 basis functions of spectral reflectances of the color chips of the reference chart 55 which are read in advance in the digital camera 54 from the chart data record memory card attached to the reference chart 55 , the expansion coefficients for the bases of the color chips and the basis functions of the spectral reflectances of human skin color are written as header data of shooting image data.
  • the image data or various data are read from the memory card 56 mounted in the personal computer 57 so as to perform the above-described process.
  • the data are converted into RGB image data and displayed on the monitor 58 .
  • FIG. 18 is a diagram showing the concept of the format of the shooting image data stored in the memory card 56 .
  • Color chart expansion coefficient data, chip spectral reflectance basis function data and object spectral reflectance basis function data are recorded in the card as header data of one piece of image data. After the header data, the image data is recorded as RGB image data for each pixel. Each RGB channel is data of 1 byte.
  • FIG. 19 is a diagram illustrating the concept of the color conversion process.
  • the image data (RGB) signal read from the memory card 56 to the personal computer 57 are converted into the spectral reflectance of the object from color chip expansion coefficient data recorded as image header data, chip spectral reflectance basis function data, object spectral reflectance basis function data, and chart shooting data.
  • the spectral reflectance is converted into XYZ values with use of observation-site illumination data and color matching functions stored in the computer, and further converted into RGB image data to be input to a monitor, using the monitor characteristics data, to be displayed as a color image on the CRT monitor.
  • the color image processing apparatus of the present invention can estimate the spectral reflectance of an object from the object shooting signal Q and reference chart shooting signal G, shot by the color image input device under the same illumination condition, the color chips basis functions vn( ⁇ ) which can expand the spectral reflectances of every color chip of the reference chart pre-stored, the expansion coefficient B of each color chip, and the basis function of the spectral reflectance of the object.
  • the conditions for being able to estimate the spectral reflectance of an object without error are that the basis functions of the spectral reflectance of the object can be expanded by the color chip basis functions vn( ⁇ ) of the reference chart, and that the color image input device has a certain number of bands, which is more than the number of basis functions of the spectral reflectances of the object.
  • the spectral reflectance of the object can be estimated.
  • the present invention it is possible to provide a color image processing apparatus for estimating the spectral reflectance of the object from the color image signal of the object, obtained by the input device even if the spectral sensitivities of the input device and the shooting-site illumination spectrum used when the color image signal is input are not known.

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Cited By (45)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20010052904A1 (en) * 2000-06-16 2001-12-20 Dainichiseika Color & Chemicals Mfg Co., Ltd CCM calculating system, CCM calculating method and recording medium
US20030067545A1 (en) * 2001-08-29 2003-04-10 L'oreal Device and method for acquiring an image of a portion of the human body
US20030098916A1 (en) * 2001-08-22 2003-05-29 Fuji Photo Film Co., Ltd. Method and apparatus for determining color correction matrix and method and apparatus for photographing image
US20030185438A1 (en) * 1997-09-16 2003-10-02 Olympus Optical Co., Ltd. Color image processing apparatus
US20030206633A1 (en) * 2002-05-01 2003-11-06 Minolta Co. Ltd. Image encrypting method, and image decrypting method
US6766050B1 (en) * 1999-08-03 2004-07-20 Olympus Corporation Color reproducing system capable of performing selection about whether or not predetermined processing is performed on color image data
US6856354B1 (en) * 1998-11-13 2005-02-15 Olympus Optical Co., Ltd. Color reproducing system for reproducing a color of an object under illumination light
US20050078554A1 (en) * 1996-12-20 2005-04-14 Bittleston Simon H. Control devices for controlling the position of a marine seismic streamer
US20050093995A1 (en) * 2003-09-19 2005-05-05 Seiko Epson Corporation Video recording method, video recording apparatus, video recording medium, video display method, and video display apparatus
US20050111017A1 (en) * 2002-07-30 2005-05-26 Canon Kabushiki Kaisha Image processing system, apparatus, and method, and color reproduction method
US6906834B1 (en) * 1999-10-14 2005-06-14 Mitsubishi Denki Kabushiki Kaisha Color conversion device and method of manufacturing the same
US20050188908A1 (en) * 1998-10-01 2005-09-01 Oyvind Hillesund Seismic data acquisiton equipment control system
US6961086B1 (en) * 1999-02-08 2005-11-01 Fuji-Photo Film Co., Ltd Photographing apparatus for correcting white balance of an image signal and a color correction coefficient of image data
US6980231B1 (en) * 1999-05-25 2005-12-27 Olympus Corporation Color reproduction system
US20060181543A1 (en) * 2003-10-07 2006-08-17 Olympus Corporation Image display apparatus and image display method
US20060181681A1 (en) * 2003-10-07 2006-08-17 Olympus Corporation Multiband camera control apparatus and multiband camera control method
US20060188150A1 (en) * 2003-10-07 2006-08-24 Olympus Corporation Image display device and image display method
DE102004033585A8 (de) 2004-07-06 2006-08-24 Axana-Müller, Susi Verfahren und System zur automatischen Bestimmung von Farben sowie ein entsprechendes Computerprogramm und ein entsprechendes computerlesbares Speichermedium
US7102648B1 (en) 2000-04-11 2006-09-05 Rah Color Technologies Llc Methods and apparatus for calibrating a color display
US20060227657A1 (en) * 2005-04-08 2006-10-12 Tallak Tveide Apparatus and methods for seismic streamer positioning
US7136187B1 (en) * 1999-08-04 2006-11-14 Fuji Photo Film Co., Ltd Color correcting relation extracting method and color correction method
US20070043527A1 (en) * 2005-08-18 2007-02-22 Shuxue Quan Systems, methods, and apparatus for image processing, for color classification, and for skin color detection
EP1763219A1 (en) * 2005-09-12 2007-03-14 Canon Kabushiki Kaisha Image processing apparatus and image processing method
US7280251B1 (en) 1996-02-26 2007-10-09 Rah Color Technologies System and method for calibrating color printers
US20080278592A1 (en) * 2004-04-05 2008-11-13 Mitsubishi Electric Corporation Imaging Device
US20080285844A1 (en) * 2007-05-02 2008-11-20 The Regents Of The University Of California Method and apparatus for use of an universal color index (uci): a color appearance system calibrated to reflectance spectra
US20090141976A1 (en) * 2005-07-13 2009-06-04 Nec Corporation Color Correction Method and Color Correction Apparatus
US20090180689A1 (en) * 2008-01-11 2009-07-16 Olympus Corporation Color reproduction device, color reproduction method, and computer-readable recording medium recorded with color reproduction program
US20090231421A1 (en) * 2006-08-24 2009-09-17 Olympus Corporation Image processing apparatus and image processing method
EP1570684A4 (en) * 2002-12-13 2010-06-30 Color Savvy Systems Ltd APPLICATION METHOD FOR AN ELECTRONIC IMAGING APPARATUS FOR COLOR MEASUREMENT
US20100214421A1 (en) * 2009-02-26 2010-08-26 Di Qu Skin Color Measurement
US20100328740A1 (en) * 2008-02-22 2010-12-30 Nec Corporation Method, apparatus and program for color image processing
US20110149109A1 (en) * 2009-12-21 2011-06-23 Electronics And Telecommunications Research Institute Apparatus and method for converting color of taken image
WO2013101639A1 (en) * 2011-12-28 2013-07-04 Dolby Laboratories Licensing Corporation Spectral synthesis for image capture device processing
US8792297B2 (en) 2010-07-02 2014-07-29 Pgs Geophysical As Methods for gathering marine geophysical data
WO2015113610A1 (en) * 2014-01-30 2015-08-06 Hewlett-Packard Development Company L.P. Color model
US9194746B1 (en) 2013-09-04 2015-11-24 Videk, Inc. System for measuring deviation of printed color at a selected location on a moving substrate from a target color
US9423519B2 (en) 2013-03-14 2016-08-23 Pgs Geophysical As Automated lateral control of seismic streamers
US9516288B2 (en) 2005-08-31 2016-12-06 Rah Color Technologies Llc Color calibration of color image rendering devices
US20170126943A1 (en) * 2008-01-02 2017-05-04 The Regents Of The University Of California Cellscope apparatus and methods for imaging
US20170278257A1 (en) * 2016-03-25 2017-09-28 Fuji Xerox Co., Ltd. Data processing apparatus, color identification method, non-transitory computer readable medium, and color chart
US10184837B2 (en) 2013-07-24 2019-01-22 Access Business Group International Llc Chart for evaluating skin color and its application to efficacy evaluation of anti-aging and skin lightening products
CN113260846A (zh) * 2018-08-16 2021-08-13 Essenlix 公司 表面颜色和液体接触角成像
US11193830B2 (en) * 2013-04-04 2021-12-07 Instrument Systems Optische Messtechnik Gmbh Spectrocolorimeter imaging system
US11727599B2 (en) 2018-03-22 2023-08-15 Toppan Printing Co., Ltd. Color correspondence information generating system, program, and method of generating color correspondence information

Families Citing this family (100)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3551854B2 (ja) 1999-09-01 2004-08-11 ミノルタ株式会社 デジタル撮影装置、画像データ処理装置、デジタル撮影方法および記録媒体
JP2001309356A (ja) * 2000-04-27 2001-11-02 Ntt Communications Kk 遠隔地状況閲覧方法並びにその装置
JP2002135789A (ja) * 2000-10-19 2002-05-10 Canon Inc 撮像装置及びその信号処理方法及びその信号処理を実行するモジュールを有する記憶媒体
US6956966B2 (en) * 2001-04-03 2005-10-18 Electronics For Imaging, Inc. Method and apparatus for automated image correction for digital image acquisition
JP2003348501A (ja) 2002-05-23 2003-12-05 Olympus Optical Co Ltd 画像表示装置
CA2443206A1 (en) 2003-09-23 2005-03-23 Ignis Innovation Inc. Amoled display backplanes - pixel driver circuits, array architecture, and external compensation
JP2005201693A (ja) 2004-01-13 2005-07-28 Olympus Corp 色票処理装置、色票処理方法及び色票処理プログラム
US7522322B2 (en) * 2004-08-19 2009-04-21 Carestream Health, Inc. Apparatus for dental shade measurement
CA2490858A1 (en) 2004-12-07 2006-06-07 Ignis Innovation Inc. Driving method for compensated voltage-programming of amoled displays
US9275579B2 (en) 2004-12-15 2016-03-01 Ignis Innovation Inc. System and methods for extraction of threshold and mobility parameters in AMOLED displays
US9280933B2 (en) 2004-12-15 2016-03-08 Ignis Innovation Inc. System and methods for extraction of threshold and mobility parameters in AMOLED displays
US10013907B2 (en) 2004-12-15 2018-07-03 Ignis Innovation Inc. Method and system for programming, calibrating and/or compensating, and driving an LED display
US10012678B2 (en) 2004-12-15 2018-07-03 Ignis Innovation Inc. Method and system for programming, calibrating and/or compensating, and driving an LED display
WO2006063448A1 (en) 2004-12-15 2006-06-22 Ignis Innovation Inc. Method and system for programming, calibrating and driving a light emitting device display
US8576217B2 (en) 2011-05-20 2013-11-05 Ignis Innovation Inc. System and methods for extraction of threshold and mobility parameters in AMOLED displays
US9799246B2 (en) 2011-05-20 2017-10-24 Ignis Innovation Inc. System and methods for extraction of threshold and mobility parameters in AMOLED displays
GB0504520D0 (en) * 2005-03-04 2005-04-13 Chrometrics Ltd Reflectance spectra estimation and colour space conversion using reference reflectance spectra
WO2006106509A2 (en) * 2005-04-04 2006-10-12 Hadasit Ltd. Medical imaging method and system
JP5355080B2 (ja) 2005-06-08 2013-11-27 イグニス・イノベイション・インコーポレーテッド 発光デバイス・ディスプレイを駆動するための方法およびシステム
CA2518276A1 (en) 2005-09-13 2007-03-13 Ignis Innovation Inc. Compensation technique for luminance degradation in electro-luminance devices
JP4692190B2 (ja) * 2005-09-29 2011-06-01 凸版印刷株式会社 分光反射率推定方法、分光反射率推定装置、ならびに分光反射率推定プログラム
US8208758B2 (en) * 2005-10-05 2012-06-26 Qualcomm Incorporated Video sensor-based automatic region-of-interest detection
US8019170B2 (en) * 2005-10-05 2011-09-13 Qualcomm, Incorporated Video frame motion-based automatic region-of-interest detection
US9489891B2 (en) 2006-01-09 2016-11-08 Ignis Innovation Inc. Method and system for driving an active matrix display circuit
US9269322B2 (en) 2006-01-09 2016-02-23 Ignis Innovation Inc. Method and system for driving an active matrix display circuit
JP4798354B2 (ja) * 2006-02-02 2011-10-19 凸版印刷株式会社 分光反射率推定方法、分光反射率推定装置および分光反射率推定プログラム
US8477121B2 (en) 2006-04-19 2013-07-02 Ignis Innovation, Inc. Stable driving scheme for active matrix displays
US8009884B2 (en) * 2006-06-20 2011-08-30 Shiu-Shin Chio Method and apparatus for diagnosing conditions using tissue color
CA2556961A1 (en) 2006-08-15 2008-02-15 Ignis Innovation Inc. Oled compensation technique based on oled capacitance
JP4894489B2 (ja) * 2006-12-07 2012-03-14 富士ゼロックス株式会社 画像処理装置及び画像読取装置
US7860304B2 (en) * 2006-12-11 2010-12-28 Canon Kabushiki Kaisha Constructing basis functions using sensor wavelength dependence
JP2010517460A (ja) * 2007-01-29 2010-05-20 ジョンイル パク マルチスペクトル映像取得方法およびその装置
WO2008143173A1 (ja) * 2007-05-18 2008-11-27 Shima Seiki Manufacturing, Ltd. カラーマッチング方法とカラーマッチングシステム
JP5111295B2 (ja) * 2007-09-12 2013-01-09 キヤノン株式会社 色処理装置およびその方法
US8019153B2 (en) * 2007-09-18 2011-09-13 Canon Kabushiki Kaisha Wide luminance range colorimetrically accurate profile generation method
CA2637343A1 (en) 2008-07-29 2010-01-29 Ignis Innovation Inc. Improving the display source driver
US9370075B2 (en) 2008-12-09 2016-06-14 Ignis Innovation Inc. System and method for fast compensation programming of pixels in a display
US8478029B2 (en) * 2009-05-26 2013-07-02 Tandent Vision Science, Inc. Multi-resolution analysis in image segregation
CA2669367A1 (en) 2009-06-16 2010-12-16 Ignis Innovation Inc Compensation technique for color shift in displays
US9311859B2 (en) 2009-11-30 2016-04-12 Ignis Innovation Inc. Resetting cycle for aging compensation in AMOLED displays
CA2688870A1 (en) 2009-11-30 2011-05-30 Ignis Innovation Inc. Methode and techniques for improving display uniformity
US10319307B2 (en) 2009-06-16 2019-06-11 Ignis Innovation Inc. Display system with compensation techniques and/or shared level resources
US9384698B2 (en) 2009-11-30 2016-07-05 Ignis Innovation Inc. System and methods for aging compensation in AMOLED displays
JP4987045B2 (ja) * 2009-08-20 2012-07-25 オリンパス株式会社 色票処理装置、色票処理方法及び色票処理プログラム
US10996258B2 (en) 2009-11-30 2021-05-04 Ignis Innovation Inc. Defect detection and correction of pixel circuits for AMOLED displays
US8803417B2 (en) 2009-12-01 2014-08-12 Ignis Innovation Inc. High resolution pixel architecture
US10089921B2 (en) 2010-02-04 2018-10-02 Ignis Innovation Inc. System and methods for extracting correlation curves for an organic light emitting device
US9881532B2 (en) 2010-02-04 2018-01-30 Ignis Innovation Inc. System and method for extracting correlation curves for an organic light emitting device
US10163401B2 (en) 2010-02-04 2018-12-25 Ignis Innovation Inc. System and methods for extracting correlation curves for an organic light emitting device
US10176736B2 (en) 2010-02-04 2019-01-08 Ignis Innovation Inc. System and methods for extracting correlation curves for an organic light emitting device
US20140313111A1 (en) 2010-02-04 2014-10-23 Ignis Innovation Inc. System and methods for extracting correlation curves for an organic light emitting device
CA2692097A1 (en) 2010-02-04 2011-08-04 Ignis Innovation Inc. Extracting correlation curves for light emitting device
JP4977923B2 (ja) 2010-03-03 2012-07-18 日本電気株式会社 アクティブ型車両視界補助装置及び車両視界補助方法
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JP5761762B2 (ja) * 2010-05-11 2015-08-12 国立大学法人群馬大学 分光反射率測定装置、及び分光反射率測定方法
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US9886899B2 (en) 2011-05-17 2018-02-06 Ignis Innovation Inc. Pixel Circuits for AMOLED displays
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US20140368491A1 (en) 2013-03-08 2014-12-18 Ignis Innovation Inc. Pixel circuits for amoled displays
US9530349B2 (en) 2011-05-20 2016-12-27 Ignis Innovations Inc. Charged-based compensation and parameter extraction in AMOLED displays
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EP3547301A1 (en) 2011-05-27 2019-10-02 Ignis Innovation Inc. Systems and methods for aging compensation in amoled displays
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US9324268B2 (en) 2013-03-15 2016-04-26 Ignis Innovation Inc. Amoled displays with multiple readout circuits
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US8937632B2 (en) 2012-02-03 2015-01-20 Ignis Innovation Inc. Driving system for active-matrix displays
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US10657895B2 (en) 2015-07-24 2020-05-19 Ignis Innovation Inc. Pixels and reference circuits and timing techniques
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US10373554B2 (en) 2015-07-24 2019-08-06 Ignis Innovation Inc. Pixels and reference circuits and timing techniques
CA2900170A1 (en) 2015-08-07 2017-02-07 Gholamreza Chaji Calibration of pixel based on improved reference values
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JPWO2019159565A1 (ja) * 2018-02-13 2021-01-07 株式会社ニコン 情報管理装置、端末、情報管理システムおよびプログラム
US11114059B2 (en) * 2018-11-02 2021-09-07 Portrait Displays, Inc. System and method for color calibration
JP6964616B2 (ja) * 2019-03-22 2021-11-10 日本碍子株式会社 セラミックス焼成体の特性推定方法
JP7082379B2 (ja) * 2019-03-29 2022-06-08 株式会社サンヨー・シーワィピー 調整画像データ生成装置、色差調整画像表示システム、色差調整画像データ生成方法、色差調整画像データ生成プログラムおよび色差調整画像表示方法
US11727476B2 (en) 2020-01-22 2023-08-15 Lydia Ann Colby Color rendering

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09172649A (ja) 1995-12-19 1997-06-30 Olympus Optical Co Ltd カラー画像記録再生システム
US5805213A (en) * 1995-12-08 1998-09-08 Eastman Kodak Company Method and apparatus for color-correcting multi-channel signals of a digital camera
US5956015A (en) * 1995-12-18 1999-09-21 Ricoh Company, Ltd. Method and system for correcting color display based upon ambient light
US6043909A (en) * 1996-02-26 2000-03-28 Imagicolor Corporation System for distributing and controlling color reproduction at multiple sites

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6081254A (en) * 1993-08-12 2000-06-27 Hitachi, Ltd. Color correction system of imaging apparatus
US5852675A (en) * 1995-04-14 1998-12-22 Kiyoshi Matsuo Color chart for image correction and method of color correction
JP3829363B2 (ja) * 1996-06-14 2006-10-04 コニカミノルタホールディングス株式会社 電子カメラ
JP3843170B2 (ja) * 1997-08-25 2006-11-08 富士写真フイルム株式会社 カラーコレクション関数設定方法
JP4076248B2 (ja) * 1997-09-09 2008-04-16 オリンパス株式会社 色再現装置
JPH1196333A (ja) * 1997-09-16 1999-04-09 Olympus Optical Co Ltd カラー画像処理装置
JP2001045516A (ja) * 1999-08-03 2001-02-16 Olympus Optical Co Ltd 色再現システム

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5805213A (en) * 1995-12-08 1998-09-08 Eastman Kodak Company Method and apparatus for color-correcting multi-channel signals of a digital camera
US5956015A (en) * 1995-12-18 1999-09-21 Ricoh Company, Ltd. Method and system for correcting color display based upon ambient light
JPH09172649A (ja) 1995-12-19 1997-06-30 Olympus Optical Co Ltd カラー画像記録再生システム
US5864364A (en) * 1995-12-19 1999-01-26 Olympus Optical Co., Ltd. Color image recording and reproducing system
US6043909A (en) * 1996-02-26 2000-03-28 Imagicolor Corporation System for distributing and controlling color reproduction at multiple sites

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
"A Generalised Method For Spectral Scanner Characterization" by Lindsay W. MacDonald and M. Ronnier Luo, Colour Image Science, Exploiting Digital Media, pp. 116-131, 2002, John Wiley & Sons Ltd.
Chang et al. "A color constancy model for advanced televesion cameras" IEEE Transction on Broadcasting vol. 38 pp. 90-97, Jun. 1992.* *
Gauray Sharma and H. Joel Trussel, "Set Theoretic Estimation in Color Scanner Characterization", Journal of Electronic Imaging, vol. 5(4), 479-489, Oct. 1996.
Ho et al. "seperating a color signal into illumination and Surface reflectance componets : theory and applications" IEEE transactions on Pattern Analysis and Machine Intelligence vol. 12 pp. 966-977, Oct. 1990.* *
Journal of Imaging Science and Technology, vol. 40, No. 5, Sep., Oct., 1996, pp. 422-430, Principal Component Analysis of Skin Color and Its Application to Colorimetric Color Reproduction on CRT Display and Hardcopy.

Cited By (108)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7280251B1 (en) 1996-02-26 2007-10-09 Rah Color Technologies System and method for calibrating color printers
US20050078554A1 (en) * 1996-12-20 2005-04-14 Bittleston Simon H. Control devices for controlling the position of a marine seismic streamer
US7822552B2 (en) 1996-12-20 2010-10-26 Westerngeco L.L.C. Control devices for controlling the position of a marine seismic streamer
US20050209783A1 (en) * 1996-12-20 2005-09-22 Bittleston Simon H Control devices for controlling the position of a marine seismic streamer
US9395459B2 (en) 1996-12-20 2016-07-19 Westerngeco, L.L.C. Control devices for controlling the position of a marine seismic streamer
US9395458B2 (en) 1996-12-20 2016-07-19 Westerngeco, L.L.C. Control devices for controlling the position of a marine seismic streamer
US20030185438A1 (en) * 1997-09-16 2003-10-02 Olympus Optical Co., Ltd. Color image processing apparatus
US7251362B2 (en) 1997-09-16 2007-07-31 Olympus Optical Co., Ltd. Color image processing apparatus
US20060061841A1 (en) * 1997-09-16 2006-03-23 Olympus Optical Co., Ltd. Color image processing apparatus
US7010162B2 (en) * 1997-09-16 2006-03-07 Olympus Optical Co., Ltd. Color image processing apparatus
US8743655B2 (en) 1998-01-10 2014-06-03 Oyvind Hillesund Control system for positioning of marine seismic streamers
US20070041272A1 (en) * 1998-01-10 2007-02-22 Westerngeco L.L.C. Control system for positioning of marine seismic streamers
US8230801B2 (en) 1998-01-10 2012-07-31 Westerngeco L.L.C. Control system for positioning of marine seismic streamers
US20090238035A1 (en) * 1998-01-10 2009-09-24 Westerngeco, L.L.C. Control system for positioning of marine seismic streamers
US20050188908A1 (en) * 1998-10-01 2005-09-01 Oyvind Hillesund Seismic data acquisiton equipment control system
US7293520B2 (en) 1998-10-01 2007-11-13 Westerngeco, L.L.C. Control system for positioning of a marine seismic streamers
US7222579B2 (en) 1998-10-01 2007-05-29 Westerngeco, L.L.C. Control system for positioning of marine seismic streamers
US7080607B2 (en) 1998-10-01 2006-07-25 Westerngeco, L.L.C. Seismic data acquisiton equipment control system
US20060231007A1 (en) * 1998-10-01 2006-10-19 Westerngeco, L.L.C. Control system for positioning of a marine seismic streamers
US20060231006A1 (en) * 1998-10-01 2006-10-19 Westerngeco, L.L.C. Control system for positioning of marine seismic streamers
US6856354B1 (en) * 1998-11-13 2005-02-15 Olympus Optical Co., Ltd. Color reproducing system for reproducing a color of an object under illumination light
US6961086B1 (en) * 1999-02-08 2005-11-01 Fuji-Photo Film Co., Ltd Photographing apparatus for correcting white balance of an image signal and a color correction coefficient of image data
US6980231B1 (en) * 1999-05-25 2005-12-27 Olympus Corporation Color reproduction system
US20040240728A1 (en) * 1999-08-03 2004-12-02 Haruko Saikawa Color reproducing system capable of performing selection about whether or not predetermined processing is performed on color image data
US7020331B2 (en) 1999-08-03 2006-03-28 Olympus Corporation Color reproducing system capable of performing selection about whether or not predetermined processing is performed on color image data
US6766050B1 (en) * 1999-08-03 2004-07-20 Olympus Corporation Color reproducing system capable of performing selection about whether or not predetermined processing is performed on color image data
US7136187B1 (en) * 1999-08-04 2006-11-14 Fuji Photo Film Co., Ltd Color correcting relation extracting method and color correction method
US6906834B1 (en) * 1999-10-14 2005-06-14 Mitsubishi Denki Kabushiki Kaisha Color conversion device and method of manufacturing the same
US8665289B2 (en) 2000-04-11 2014-03-04 RAH Color Technology LLC Methods and apparatus for calibrating a color display
US20060221093A1 (en) * 2000-04-11 2006-10-05 Holub Richard A Methods and apparatus for calibrating a color display
US9767763B2 (en) 2000-04-11 2017-09-19 Rah Color Technologies Llc Methods and apparatus for calibrating a color display
US8009175B2 (en) 2000-04-11 2011-08-30 Rah Color Technologies Llc Methods and apparatus for calibrating a color display
US8279236B2 (en) 2000-04-11 2012-10-02 Rah Color Technologies Llc Methods and apparatus for calibrating a color display
US7710433B2 (en) 2000-04-11 2010-05-04 Rah Color Technologies Llc Methods and apparatus for calibrating a color display
US10008180B2 (en) 2000-04-11 2018-06-26 Rah Color Technologies Llc Methods and apparatus for calibrating a color display
US7102648B1 (en) 2000-04-11 2006-09-05 Rah Color Technologies Llc Methods and apparatus for calibrating a color display
US9500527B2 (en) 2000-04-11 2016-11-22 Rah Color Technologies Llc Methods and apparatus for calibrating a color display
US7148900B2 (en) * 2000-06-16 2006-12-12 Danichisekia Color And Chemicals Mfg. Co., Ltd. CCM calculating system, CCM calculating method and recording medium
US20010052904A1 (en) * 2000-06-16 2001-12-20 Dainichiseika Color & Chemicals Mfg Co., Ltd CCM calculating system, CCM calculating method and recording medium
US20030098916A1 (en) * 2001-08-22 2003-05-29 Fuji Photo Film Co., Ltd. Method and apparatus for determining color correction matrix and method and apparatus for photographing image
US7265781B2 (en) * 2001-08-22 2007-09-04 Fujifilm Corporation Method and apparatus for determining a color correction matrix by minimizing a color difference maximum or average value
US20030067545A1 (en) * 2001-08-29 2003-04-10 L'oreal Device and method for acquiring an image of a portion of the human body
US20030206633A1 (en) * 2002-05-01 2003-11-06 Minolta Co. Ltd. Image encrypting method, and image decrypting method
US7415612B2 (en) * 2002-05-01 2008-08-19 Minolta Co., Ltd. Image encrypting method, and image decrypting method
US7986438B2 (en) * 2002-07-30 2011-07-26 Canon Kabushiki Kaisha Image processing system, apparatus, and method, and color reproduction method
US7480083B2 (en) * 2002-07-30 2009-01-20 Canon Kabushiki Kaisha Image processing system, apparatus, and method, and color reproduction method
US20090080009A1 (en) * 2002-07-30 2009-03-26 Canon Kabushiki Kaisha Image processing system, apparatus, and method, and color reproduction method
US20050111017A1 (en) * 2002-07-30 2005-05-26 Canon Kabushiki Kaisha Image processing system, apparatus, and method, and color reproduction method
EP1570684A4 (en) * 2002-12-13 2010-06-30 Color Savvy Systems Ltd APPLICATION METHOD FOR AN ELECTRONIC IMAGING APPARATUS FOR COLOR MEASUREMENT
US20050093995A1 (en) * 2003-09-19 2005-05-05 Seiko Epson Corporation Video recording method, video recording apparatus, video recording medium, video display method, and video display apparatus
US7417642B2 (en) 2003-10-07 2008-08-26 Olympus Corporation Image display device and image display method
US20060188150A1 (en) * 2003-10-07 2006-08-24 Olympus Corporation Image display device and image display method
US20060181543A1 (en) * 2003-10-07 2006-08-17 Olympus Corporation Image display apparatus and image display method
US7768560B2 (en) 2003-10-07 2010-08-03 Olympus Corporation multiband camera control apparatus and multiband camera control method
US20060181681A1 (en) * 2003-10-07 2006-08-17 Olympus Corporation Multiband camera control apparatus and multiband camera control method
US7663668B2 (en) * 2004-04-05 2010-02-16 Mitsubishi Electric Corporation Imaging device
US20080278592A1 (en) * 2004-04-05 2008-11-13 Mitsubishi Electric Corporation Imaging Device
DE102004033585A8 (de) 2004-07-06 2006-08-24 Axana-Müller, Susi Verfahren und System zur automatischen Bestimmung von Farben sowie ein entsprechendes Computerprogramm und ein entsprechendes computerlesbares Speichermedium
US20060227657A1 (en) * 2005-04-08 2006-10-12 Tallak Tveide Apparatus and methods for seismic streamer positioning
US7450467B2 (en) 2005-04-08 2008-11-11 Westerngeco L.L.C. Apparatus and methods for seismic streamer positioning
US8023736B2 (en) 2005-07-13 2011-09-20 Nec Corporation Color correction method and color correction apparatus
EP1906674A4 (en) * 2005-07-13 2011-06-22 Nec Corp COLOR CORRECTION AND COLOR CORRECTION DEVICE
US20090141976A1 (en) * 2005-07-13 2009-06-04 Nec Corporation Color Correction Method and Color Correction Apparatus
US8855412B2 (en) 2005-08-18 2014-10-07 Qualcomm Incorporated Systems, methods, and apparatus for image processing, for color classification, and for skin color detection
US20070043527A1 (en) * 2005-08-18 2007-02-22 Shuxue Quan Systems, methods, and apparatus for image processing, for color classification, and for skin color detection
US8154612B2 (en) * 2005-08-18 2012-04-10 Qualcomm Incorporated Systems, methods, and apparatus for image processing, for color classification, and for skin color detection
US10560676B2 (en) 2005-08-31 2020-02-11 Rah Color Technologies Llc Color calibration of color image rendering devices
US9894340B2 (en) 2005-08-31 2018-02-13 Rah Color Technologies Llc Color calibration of color image rendering devices
US9516288B2 (en) 2005-08-31 2016-12-06 Rah Color Technologies Llc Color calibration of color image rendering devices
US10038884B2 (en) 2005-08-31 2018-07-31 Rah Color Technologies Llc Color calibration of color image rendering devices
US20070058223A1 (en) * 2005-09-12 2007-03-15 Canon Kabushiki Kaisha Image processing method and image processing apparatus, and program thereof
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US7751618B2 (en) 2005-09-12 2010-07-06 Canon Kabushiki Kaisha Image processing method and image processing apparatus, and program thereof
CN100496087C (zh) * 2005-09-12 2009-06-03 佳能株式会社 图像处理方法和图像处理设备
US8068133B2 (en) * 2006-08-24 2011-11-29 Olympus Corporation Image processing apparatus and image processing method
US20090231421A1 (en) * 2006-08-24 2009-09-17 Olympus Corporation Image processing apparatus and image processing method
US8520936B2 (en) * 2007-05-02 2013-08-27 The Regents Of The University Of California Method and apparatus for use of an universal color index (UCI): a color appearance system calibrated to reflectance spectra
US20080285844A1 (en) * 2007-05-02 2008-11-20 The Regents Of The University Of California Method and apparatus for use of an universal color index (uci): a color appearance system calibrated to reflectance spectra
US20170126943A1 (en) * 2008-01-02 2017-05-04 The Regents Of The University Of California Cellscope apparatus and methods for imaging
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US20090180689A1 (en) * 2008-01-11 2009-07-16 Olympus Corporation Color reproduction device, color reproduction method, and computer-readable recording medium recorded with color reproduction program
US20100328740A1 (en) * 2008-02-22 2010-12-30 Nec Corporation Method, apparatus and program for color image processing
US9485391B2 (en) 2008-02-22 2016-11-01 Nec Corporation Method, apparatus and program for restoring and correcting surface reflectance with color image processing
US20100214421A1 (en) * 2009-02-26 2010-08-26 Di Qu Skin Color Measurement
US8319857B2 (en) 2009-02-26 2012-11-27 Access Business Group International Llc Apparatus and method for correcting digital color photographs
US20110149109A1 (en) * 2009-12-21 2011-06-23 Electronics And Telecommunications Research Institute Apparatus and method for converting color of taken image
US8792297B2 (en) 2010-07-02 2014-07-29 Pgs Geophysical As Methods for gathering marine geophysical data
US9851464B2 (en) 2010-07-02 2017-12-26 Pgs Geophysical As Methods for gathering marine geophysical data
US9479750B2 (en) 2011-12-28 2016-10-25 Dolby Laboratories Licensing Corporation Spectral synthesis for image capture device processing
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US8929654B2 (en) 2011-12-28 2015-01-06 Dolby Laboratories Licensing Corporation Spectral image processing
US9423519B2 (en) 2013-03-14 2016-08-23 Pgs Geophysical As Automated lateral control of seismic streamers
US10054705B2 (en) 2013-03-14 2018-08-21 Pgs Geophysical As Automated lateral control of seismic streamers
US11119236B2 (en) 2013-03-14 2021-09-14 Pgs Geophysical As Automated lateral control of seismic streamers
US11193830B2 (en) * 2013-04-04 2021-12-07 Instrument Systems Optische Messtechnik Gmbh Spectrocolorimeter imaging system
US10184837B2 (en) 2013-07-24 2019-01-22 Access Business Group International Llc Chart for evaluating skin color and its application to efficacy evaluation of anti-aging and skin lightening products
US9194746B1 (en) 2013-09-04 2015-11-24 Videk, Inc. System for measuring deviation of printed color at a selected location on a moving substrate from a target color
US9936104B2 (en) 2014-01-30 2018-04-03 Hewlett-Packard Development Company, L.P. Printing process and printing system to display print preview with updated color model
WO2015113610A1 (en) * 2014-01-30 2015-08-06 Hewlett-Packard Development Company L.P. Color model
US20170278257A1 (en) * 2016-03-25 2017-09-28 Fuji Xerox Co., Ltd. Data processing apparatus, color identification method, non-transitory computer readable medium, and color chart
US10181198B2 (en) * 2016-03-25 2019-01-15 Fuji Xerox Co., Ltd. Data processing apparatus, color identification method, non-transitory computer readable medium, and color chart
US11727599B2 (en) 2018-03-22 2023-08-15 Toppan Printing Co., Ltd. Color correspondence information generating system, program, and method of generating color correspondence information
CN113260846A (zh) * 2018-08-16 2021-08-13 Essenlix 公司 表面颜色和液体接触角成像
US12393004B2 (en) 2018-08-16 2025-08-19 Essenlix Corporation Color imaging based assay

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